Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Computer experiments”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 1,711 records · Page 95

How Much is Remembered as a Function of Presentation Modality?

According to a widespread claim often used for teaching recommendations, students remember 10 percent of what they read, 20 percent of what they hear, 30 percent of what they see, and 50 percent of what they see and hear. Clearly, the percentages cannot be correct, and there is no empirical evidence even for the ordering. To investigate the ordering, we used a laboratory paradigm that has already revealed some findings regarding the ordering of modalities for remembering information. In this paradigm, subjects are given messages instructing them to move in a grid of four stacked matrices by clicking a computer mouse. The current experiment compared 3 modalities presented either once, see (visual arrows), hear (auditory words), read (visual words); twice in succession, see see, hear hear, read read; or in two different successive modalities, see hear, hear see, see read, read see, hear read, read hear. We found better performance for messages presented twice than for those presented once, regardless of modality. For the twice-presented messages performance varied as a function of the second modality, with best performance for see and worst for read.

information↗

High-precision predictions of properties of chemically disordered crystals

Multiple scattering theory (MST) combined with density functional theory (DFT) allows to predict properties of chemically disordered materials from the first principles. However, such predictions often suffer from the systematic errors, which depend on crystal geometry. Each computed property of a particular crystal structure typically has a relatively small random error and a larger systematic error. Cancellation of systematic errors allows more accurate predictions. We propose a computational methodology based on the subtraction of the systematic errors in MST. To exemplify it, we apply it to the precipitated alloys. Considering precipitation strengthening in Ni superalloys, we compute the relative enthalpies of the competing Ni_3(Al_{1-x}Ti_x)_1 crystal structures with a chemical disorder on the Al+Ti sublattice. Such predicted composition-structure-property dependencies are useful for the guided design of the next-generation alloys with improved strength. Our predictions are validated by comparison with the results of other DFT methods (having a higher computational cost) and with experiment.

density functional theory↗

STAR'S Approach to Highly Efficient End-To-End Grid Production

STAR's RHIC computing facility provides over 15K dedicated slots for data reconstruction. This number of slots is not always sufficient to satisfy an ambitious and data-challenging physics program, and harvesting resources from outside facilities is paramount to scientific success. However, constraints of remote sites (e.g. CPU time limits) do not always provide the flexibility of a dedicated farm. STAR has a breadth of smaller datasets (both in runtime and size) that can be easily offloaded to remote facilities with many such limits. Scavenged resources can be run with efficiency comparable to that of the local production and contributes additional computing time to an experiment that runs every year and therefore needs fast turnaround. We will discuss STAR's software stack of our grid production framework including features dealing with multi-site submission, automated re-submission, job tracking, as well as new challenges and possible improvements.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Main and Fringe Field Computations for the Electrostatic Quadrupoles of the Muon g-2 Experiment Storage Ring

We consider semi-infinite electrostatic deflectors with plates of different thickness, including plates with rounded edges, and we calculate their electrostatic potential and field using conformal mappings. To validate the calculations, we compare the fringe fields of these electrostatic deflectors with fringe fields of finite electrostatic capacitors, and we extend the study to fringe fields of adjacent electrostatic deflectors with consideration of electrostatic induction, where field falloffs of semi-infinite electrostatic deflectors are slower than exponential and thus behave differently from most magnetic fringe fields. Building on the success with electrostatic deflectors, we develop a highly accurate and fully Maxwellian conformal mappings method for calculation of main fields of electrostatic particle optical elements. A remarkable advantage of this method is the possibility of rapid recalculations with geometric asymmetries and mispowered plates. We use this conformal mappings method to calculate the multipole terms of the high voltage quadrupole used in the storage ring of the Muon g-2 Experiment (FNALE- 0989). Completing the methodological framework, we present a method for extracting multipole strength falloffs of a particle optical element from a set of Fourier mode falloffs. We calculate the quadrupole strength falloff and its effective field boundary (EFB) for the Muon g-2 quadrupole, which has explained the experimentally measured tunes, while simple estimates based on a linear model exhibited discrepancies up to 2%.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

High Performance Geocomputation for Assessing Human Dynamics at Planet Scale

Settlements are key indicators of human presence on the landscape. Large scale mapping of human settlements and their morphology from very high-resolution satellite images is a critical step towards developing an interpretative understanding of population distribution and the sociocultural attributes of the built environment they live in. Convolutional neural network (CNN) based Deep Learning experiments indicates that such computations can be scaled to some of the largest high-performance computing (HPC) architectures. While early results are encouraging for developing settlement and corresponding population maps at unprecedented speed and spatial resolutions, characterizing human dynamics at planet scale with high temporal resolution will require the community to develop novel geocomputational infrastructures and ecosystems.

Bhaduri, Budhu↗

Examination of New Theory for Neutron Multiplicity Counting of Non-Point-Like Sources of Special Nuclear Material

The purpose of a nondestructive assay is to accurately verify the declared mass of special nuclear material (SNM) samples in a limited amount of time. One measurement modality is neutron multiplicity counting (NMC), which relates time-correlated neutron detection rates to the mass of SNM present. Traditional theory assumes point-like sources, which can be ill-posed for kilogram-quantity, bulk samples. Recent theory was developed to improve NMC accuracy for non-point-like samples. This work preliminarily examines the theory with measured data. The OSCAR prototype (a 3-by-4 array of 5.08-cm-thick, 5.08-cm-diameter trans-stilbene organic scintillators) measures configurations of 29.41-49.00 kg of highly enriched uranium (93wt% 235 U). Adjusted factorial moments for the emitted neutron multiplicity distributions are used to account for the shape and type of SNM being measured.

252Cf↗

Scalable Graph Analytics and HPC Operational Enhancement: Parallel Computing and ML/DL Innovations

Parallel computing plays a pivotal role in the efficient processing of large-scale graphs. Complex network analysis stands as a capti- vating research frontier, holding promise across diverse scientific domains such as sociology, biology, online media, and recommenda- tion systems. In this era, Machine Learning (ML) and Deep Learning (DL) have emerged as indispensable tools, underpinning remarkable technological achievements. Within this dynamic landscape, my research revolves around advancing parallel algorithms tailored for large-scale graph operations. To achieve this, I harness the power of cutting-edge technologies including OpenMP, MPI, HIP, and CUDA, on the High-Performance Computing (HPC) platforms to unlock optimal performance. I also apply ML/DL techniques to HPC operational data, to streamline the monitoring and maintenance of supercomputers, alleviating the complexities associated with their upkeep and enhancing user support. My research echoes the syn- ergy between parallel computing, large-scale graph analysis, and ML/DL, improving computational efficiency and user experience.

Sattar, Naw Safrin↗

Comparison of UF{sub 6} cylinder dose rate measurements and Monte Carlo calculations - 25593

In uranium compounds that contain fluorine, such as uranium hexafluoride (UF{sub 6}), neutron radiation fields are naturally created as a result of a reaction between fluorine and the alpha particle emitted by uranium. In order to gain a true appreciation for the true conditions of any system, it is vital to have access to true-to-life documented information, such as when performing dose rate calculations. This UF{sub 6} cylinder dose rate experiment aims at validating computational tools, i.e., MCNP, for predicting both the photon and neutron dose rates from tails (depleted uranium) 48Y cylinders. Two sets of measured neutron and photon dose rates are featured herein. The first set is taken of a semi-isolated single tails (UF{sub 6}) cylinder stored on the Uranium Byproduct Cylinder (UBC) storage pad at the URENCO USA (UUSA) site in Eunice, New Mexico. The second set is also from a tails cylinder, stored on the UBC pad, which is located on the bottom row inside an array of triple stacked 48Y tails cylinders. These cylinder storage scenarios are modeled in MCNP and the calculated photon and neutron dose rates are compared to the measured values. The comparisons between the MCNP predictions and the measured total dose rates show good agreement. Small differences can be attributed to incomplete filling of the cylinder, variations in density and uncertainties in the measurement precision as well as external conditions of the TLD. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Representability evaluation of fuel debris nuclear characteristics by heterogeneous core of Stacy - 14581

Decommissioning is underway in the Fukushima Daiichi Nuclear Power Station (1FNPS). Criticality control is one of the important safety issues in the decommissioning, especially during fuel debris removal. In 1FNPS, part of fuel debris might be in the form of molten-core-concrete-interaction (MCCI) product. It has been shown that the MCCI product can be critical not only under water but even with water bound in concrete. Further study of criticality characteristics by computation is being conducted to clarify its criticality risk. Furthermore, the risk assessment by computation needs validation by experiment. Japan Atomic Energy Agency is preparing critical experiments with simulated fuel debris in the Static Experiment Critical Facility (STACY), whose solution core will be converted into a new core using fuel rods and light-water moderator. It is difficult to build core configurations composed of water and fuel rods which contain homogeneous mixtures of uranium dioxide (UO{sub 2}) and structural materials of boiling light water reactors. In the modified STACY, it is being planned to simulate fuel debris by arranging UO{sub 2} fuel rods and structural material rods in water. In this study, difference in heterogeneity between the experimental core and possible fuel debris conditions is evaluated by comparing infinite multiplication factors and neutron energy spectra. (authors)

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

A Demonstration of ARCANE Reweighting: Reducing the Sign Problem in the MC@NLO Generation of $e^+ e^- \rightarrow q \bar{q} + 1\, jet$ Events

Negatively weighted events, which appear in the simulation of particle collisions, significantly increase the computational requirements of collider experiments. A new technique called ARCANE reweighting has been introduced in a companion paper to tackle this problem. This paper demonstrates the technique for the next-to-leading-order generation of $e^+ e^- \rightarrow q \bar{q} + 1\, jet$ events. By redistributing the contributions of "standard" and "hard remainder" pathways in the generator that lead to the same final event, ARCANE reweighting almost completely eliminates the negative weights problem for this process. Some thoughts on implementing the technique in other scenarios are provided.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Simulating Alpha Particles Incident on MKID Chips for Quantum Sensitivity Analysis

Superconducting quantum devices, such as microwave kinetic inductance detectors (MKIDs), are highly sensitive instruments used in quantum computing and advanced sensing technologies. However, their extreme sensitivity also makes them vulnerable to background noise from natural sources like radiation. One significant contributor to this noise is alpha particles emitted by 210Po, a radon decay daughter that accumulates on surfaces near the detector. This project investigates how alpha particles emitted from 210Po interact with MKID chips. These particles can deposit energy on the detector surface, disrupting its operation and generating false signals. Understanding the energy and behavior of these particles is crucial for improving the design and reliability of quantum devices. To explore this, we first modeled the decay chain starting from 210Pb to 210Po using differential equations. This allowed us to predict how the activity of alpha-emitting isotopes changes over time, reaching a steady state after about two years. Next, we simulated alpha particle interactions with the MKID chip using the Geant4 software toolkit. We built a detailed computer model of the detector housing, including the copper lid where alpha particles originate, the silicon chip, and a thin aluminum sensor layer. Alpha particles were emitted isotropically from just beneath the copper lid’s surface, mimicking natural decay conditions. The simulation tracked how these particles deposit energy on the chip, generating electron-hole pairs and phonons. The results provide insight into the behavior of the resultant electron-hole pairs and phonons, giving us a clear understanding of the energy deposition distribution on the chip. This work supports efforts to mitigate background noise in superconducting sensors, advancing their use in quantum computing and sensitive physics experiments.

Hall, Matthew [Fermilab; UCLA]↗

AI/ML Expo Boosting Job Performance with AI: Innovative Approaches and Success Stories

Our technology leverages artificial intelligence (AI) to enhance the user experience in High Performance Computing (HPC) environments. By analyzing user behavior and providing personalized recommendations, our AI system helps HPC users optimize their workflows and improve productivity. Additionally, we offer an advanced image similarity search feature, which utilizes AI algorithms to identify and retrieve visually similar images, saving users valuable time and effort in their research and analysis.

97 - MATHEMATICS AND COMPUTING↗

INTERSECT Architecture Specification: Use Case Design Patterns (V.0.9)

Connecting scientific instruments and robot-controlled laboratories with computing and data resources at the edge, the Cloud or the high-performance computing (HPC) center enables autonomous experiments, self-driving laboratories, smart manufacturing, and artificial intelligence (AI)-driven design, discovery and evaluation. The Self-driven Experiments for Science / Interconnected Science Ecosystem (INTERSECT) Open Architecture enables science breakthroughs using intelligent networked systems, instruments and facilities with a federated hardware/software architecture for the laboratory of the future. It relies on a novel approach, consisting of (1) science use case design patterns, (2) a system of systems architecture, and (3) a microservice architecture. This document introduces the science use case design patterns of the INTERSECT Architecture. It describes the overall background, the involved terminology and concepts, and the pattern format and classification. It further details the 12 defined patterns and provides insight into building solutions from these patterns. The document also describes the application of these patterns in the context of several INTERSECT autonomous laboratories. The target audience are computer, computational, instrument and domain science experts working in the field of autonomous experiments.

97 MATHEMATICS AND COMPUTING↗

Supersonic Combusting Jet Experiments for Code Development and Validation

Computational fluid dynamics (CFD) methods based on the Reynolds averaged Navier-Stokes (RANS) equations are extensively employed in the design of hypersonic airbreathing engines. A fundamental weakness in these methods is the accurate mathematical modeling of turbulence and turbulence-combustion interactions. This paper is one of a companion pair of papers which describe the use of the combined dual pump CARS and newly developed interferometric Rayleigh scattering optical system to acquire time-accurate turbulence and mixing data with which to aid calibration and verification of the current turbulence models. This test program consisted of a pilot laboratory-scale experiment used to develop the optical system and data acquisition techniques, and a significantly larger experiment to acquire the necessary turbulence data. The flow is an axially-symmetric, supersonic, combusting, free jet that provides good optical access, consisting of a central jet of hot "vitiated air" and a coflow jet of hydrogen or ethylene fuel. In this paper the development of both experiments is described. Facility and flow visualization data are presented for various types of flames, including the flames selected for detailed study with the CARS/Rayleigh optical techniques.

Cutler, Andrew D.↗

The Adjoint Petrov–Galerkin method for non-linear model reduction

Here, we formulate a new projection-based reduced-order modeling technique for non-linear dynamical systems. The proposed technique, which we refer to as the Adjoint Petrov–Galerkin (APG) method, is derived by decomposing the generalized coordinates of a dynamical system into a resolved coarse-scale set and an unresolved fine-scale set. A Markovian finite memory assumption within the Mori–Zwanzig formalism is then used to develop a reduced-order representation of the coarse scales. This procedure leads to a closed reduced-order model that displays commonalities with the adjoint stabilization method used in finite elements. The formulation is shown to be equivalent to a Petrov–Galerkin method with a non-linear, time-varying test basis, thus sharing some similarities with the Least-Squares Petrov–Galerkin method. Theoretical analysis examining a priori error bounds and computational cost is presented. Numerical experiments on the compressible Navier–Stokes equations demonstrate that the proposed method can lead to improvements in numerical accuracy, robustness, and computational efficiency over the Galerkin method on problems of practical interest. Improvements in numerical accuracy and computational efficiency over the Least-Squares Petrov–Galerkin method are observed in most cases.

42 ENGINEERING↗

Fast Bayesian optimization of Needle-in-a-Haystack problems using zooming memory-based initialization (ZoMBI)

Abstract Needle-in-a-Haystack problems exist across a wide range of applications including rare disease prediction, ecological resource management, fraud detection, and material property optimization. A Needle-in-a-Haystack problem arises when there is an extreme imbalance of optimum conditions relative to the size of the dataset. However, current state-of-the-art optimization algorithms are not designed with the capabilities to find solutions to these challenging multidimensional Needle-in-a-Haystack problems, resulting in slow convergence or pigeonholing into a local minimum. In this paper, we present a Zooming Memory-Based Initialization algorithm, entitled ZoMBI, that builds on conventional Bayesian optimization principles to quickly and efficiently optimize Needle-in-a-Haystack problems in both less time and fewer experiments. The ZoMBI algorithm demonstrates compute time speed-ups of 400× compared to traditional Bayesian optimization as well as efficiently discovering optima in under 100 experiments that are up to 3× more highly optimized than those discovered by similar methods.

36 MATERIALS SCIENCE↗

Trace: a high-throughput tomographic reconstruction engine for large-scale datasets

Abstract Background Modern synchrotron light sources and detectors produce data at such scale and complexity that large-scale computation is required to unleash their full power. One of the widely used imaging techniques that generates data at tens of gigabytes per second is computed tomography (CT). Although CT experiments result in rapid data generation, the analysis and reconstruction of the collected data may require hours or even days of computation time with a medium-sized workstation, which hinders the scientific progress that relies on the results of analysis. Methods We present Trace, a data-intensive computing engine that we have developed to enable high-performance implementation of iterative tomographic reconstruction algorithms for parallel computers. Trace provides fine-grained reconstruction of tomography datasets using both (thread-level) shared memory and (process-level) distributed memory parallelization. Trace utilizes a special data structure called replicated reconstruction object to maximize application performance. We also present the optimizations that we apply to the replicated reconstruction objects and evaluate them using tomography datasets collected at the Advanced Photon Source. Results Our experimental evaluations show that our optimizations and parallelization techniques can provide 158× speedup using 32 compute nodes (384 cores) over a single-core configuration and decrease the end-to-end processing time of a large sinogram (with 4501 × 1 × 22,400 dimensions) from 12.5 h to <5 min per iteration. Conclusion The proposed tomographic reconstruction engine can efficiently process large-scale tomographic data using many compute nodes and minimize reconstruction times.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

A grid-embedding transonic flow analysis computer program for wing/nacelle configurations

An efficient grid-interfacing zonal algorithm was developed for computing the three-dimensional transonic flow field about wing/nacelle configurations. the algorithm uses the full-potential formulation and the AF2 approximate factorization scheme. The flow field solution is computed using a component-adaptive grid approach in which separate grids are employed for the individual components in the multi-component configuration, where each component grid is optimized for a particular geometry such as the wing or nacelle. The wing and nacelle component grids are allowed to overlap, and flow field information is transmitted from one grid to another through the overlap region using trivariate interpolation. This report represents a discussion of the computational methods used to generate both the wing and nacelle component grids, the technique used to interface the component grids, and the method used to obtain the inviscid flow solution. Computed results and correlations with experiment are presented. also presented are discussions on the organization of the wing grid generation (GRGEN3) and nacelle grid generation (NGRIDA) computer programs, the grid interface (LK) computer program, and the wing/nacelle flow solution (TWN) computer program. Descriptions of the respective subroutines, definitions of the required input parameters, a discussion on interpretation of the output, and the sample cases illustrating application of the analysis are provided for each of the four computer programs.

Atta, E. H.↗